A GRASP for Graph Planarization

Mauricio G.C. Resende and Celso C. Ribeiro

Networks, vol.29, pp. 173-189, 1997.


A greedy randomized adaptive search procedure (GRASP) is a metaheuristic for combinatorial optimization.  In this paper, we describe a GRASP for the graph planarization problem, extending the heuristic of Goldschmidt and Takvorian [Networks 24, pp.  69-73, 1994].  We review basic concepts of GRASP:  construction and local search algorithms.  The implementation of GRASP for graph planarization is described in detail.  Computational experience on a large set of standard test problems is presented.  On almost all test problems considered, the new heuristic either matches or finds a better solution than previously described graph planarization heuristics.  In several cases, previously unknown optimal solutions are found.

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